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Numerous efforts have been made to develop cancer treatments, among which anticancer peptides (ACPs) are garnering recognition for their potential applications. While ACP screening is time-consuming and costly, in silico prediction tools provide a way to overcome these challenges. Herein, we present a deep learning model designed to screen ACPs using peptide sequences only. A contrastive learning technique was applied to enhance model performance, yielding better results than a model trained solely on binary classification loss. Furthermore, two independent encoders were employed as a replacement for data augmentation, a technique commonly used in contrastive learning. Our model achieved superior performance on five of six benchmark datasets against previous state-of-the-art models. As prediction tools advance, the potential in peptide-based cancer therapeutics increases, promising a brighter future for oncology research and patient care.<\/jats:p>","DOI":"10.1093\/bib\/bbae220","type":"journal-article","created":{"date-parts":[[2024,5,10]],"date-time":"2024-05-10T03:30:35Z","timestamp":1715311835000},"source":"Crossref","is-referenced-by-count":13,"title":["Contrastive learning for enhancing feature extraction in anticancer peptides"],"prefix":"10.1093","volume":"25","author":[{"given":"Byungjo","family":"Lee","sequence":"first","affiliation":[{"name":"Research Institute, National Cancer Center , 323, Ilsan-ro, Ilsandong-gu, Goyang, 10408 , Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongkwan","family":"Shin","sequence":"additional","affiliation":[{"name":"Research Institute, National Cancer Center , 323, Ilsan-ro, Ilsandong-gu, Goyang, 10408 , Republic of Korea"},{"name":"Department of Cancer Biomedical Science, National Cancer Center Graduate School of Cancer Science and Policy , 323, Ilsan-ro, Ilsandong-gu, Goyang, 10408 , Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2024,5,9]]},"reference":[{"key":"2024051003301965600_ref1","doi-asserted-by":"crossref","first-page":"6497","DOI":"10.1245\/s10434-022-12151-6","article-title":"GLOBOCAN 2020 report on global cancer burden: challenges and opportunities for surgical oncologists","volume":"29","author":"Deo","year":"2022","journal-title":"Ann Surg Oncol"},{"key":"2024051003301965600_ref2","doi-asserted-by":"crossref","first-page":"209","DOI":"10.3322\/caac.21660","article-title":"Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"71","author":"Sung","year":"2021","journal-title":"CA Cancer J 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